Results 51 to 60 of about 6,670,018 (306)
Modelling Risk Dependencies in Insurance Using Survival Clayton Copula [PDF]
Our aim in this paper is to show the use of survival Clayton copula as a suitable tool for modelling risk dependencies in insurance. Apurpose-built simulation of an adequate upper tail dependence can be an important part of the aggregation of risks in an
Vladimír Mucha +2 more
doaj +1 more source
Joint Distributions for Interacting Fluid Queues
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Dirk P. Kroese, Werner R. W. Scheinhardt
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This study integrates publicly available transcriptomic datasets to identify molecular signatures associated with response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer. By analyzing a combination of multiple cohorts with bioinformatics approaches, we reveal biological pathways and immune‐related features that may improve ...
Aleksandra Stanojevic +10 more
wiley +1 more source
Joint Distributions and Commutability of Observables
Let H be a Hilbert space and \({\mathcal S}\) be the space of all positive trace-class operators T on H with tr (T)\(=1\) (identified with the set of all normal states on \({\mathbb{B}}(H)\) by \(\rho_ T(A)=tr (AT))\). For an observable A on H let \(P_ T\) A be the probability distribution of A at the state T, i.e. \(P\) \(A_ T(E)=\rho_ T(\chi_ E(A))\)
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Extracellular vesicle (EV) lipidomic profiling of plasma and ascites from patients with high‐grade serous ovarian cancer and of ovarian cancer cell lines reveals enrichment of triglycerides (TGs), diacylglycerols (DGs), phosphatidylcholine (PCs), sphingomyelins (SMs), reflecting tumor metabolic reprogramming.
Shikha Rani +9 more
wiley +1 more source
Characterizations of multinomial distributions based on conditional distributions
Several characterizations of the joint multinomial distribution of two discrete random vectors are derived assuming conditional multinomial distributions.
Khoan T. Dinh +2 more
doaj +1 more source
Joint feature distributions for image correspondence [PDF]
We introduce `Joint Feature Distributions', a general statistical framework for feature based multi-image matching that explicitly models the joint probability distributions of corresponding features across several images. Conditioning on feature positions in some of the images gives well-localized distributions for their correspondents in the others ...
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Reprogramming tumor cells with LCOR mRNA nanotherapy to enhance immunotherapy
LCOR (Ligand‐dependent corepressor) mRNA encapsulated in polymeric nanoparticles restores LCOR activity in tumor cells, constraining aggressive tumor cell states and increasing tumor immunogenicity. This reprogramming makes tumor cells more vulnerable to T‐cell attack and enhances their response to immune‐checkpoint immunotherapy.
Gabriel Serra‐Mir +9 more
wiley +1 more source
Ionomycin suppresses cancer cell growth by disrupting mitochondrial transcription
In this study, we identify a new function for the selective Ca2+ ionophore, ionomycin, as an inhibitor of mitochondrial transcription. Both total and nascent RNA analyses revealed that ionomycin treatment reduces the transcription of mitochondrial genes.
Lishen Wang +10 more
wiley +1 more source
Construction of Joint Probability Distributions
Let Fi(x) and F2(y) be the distribution functions of two random variables. Frechet proved that the family of joint distributions having Fi(x) and F2(y) as marginal distributions collapses to F1(x)F2(y) if and only if either F,(x) or F2(y) is a unit step function.
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